1. Field of the Invention
This invention relates to signal processing, and in particular to analog-to-analog signal conversion using analog/multi-level memory arrays.
2. Description of Related Art
Many communication systems convert signals from one format to another. For example, audio and image processing systems often use analog-to-digital converters (ADCs) to convert analog audio or image signals to digital samples for digital processing and subsequent storage in memory or transmission along communication channels. The processed or stored digital data can then be converted back to an analog signal by digital-to-analog converters (DACs) for play-back or display, resulting in an analog-to-analog conversion. Analog-to-analog conversion can also be used to convert analog signals from one format to another format for a variety of uses such as audio transmissions or analog data encryption.
First, conversion to a suitable digital format includes sampling the analog waveform, quantizing each of the sampled values to one of M discrete levels, and encoding each quantized analog value into a binary data stream. FIG. 1 is a block diagram of a conventional ADC 100 that quantizes a sampled analog value Ain into one of M (i.e., x+1) discrete values and then encodes the discrete value into an n-bit digital output signal Dout. ADC 100 includes a reference voltage source 110, comparators 120, and an encoder 130. In ADC 100, reference voltage source 110 includes series-connected resistors R0 to Rx that generate x+1 reference voltages V0 to Vx, where x is equal to 2.sup.n -1. The reference voltages V0 to Vx represent the possible quantized levels of the sampled analog input signal Ain.
To convert analog signal Ain into the n-bit digital output signal Dout, comparators 120 simultaneously compare analog signal Ain to reference voltages V0 to Vx. The relative values of resistors R0 to Rx determine the step size between successive reference voltages. For example, if R0=R1= . . . =Rx, then the step size is the same between each reference voltage, i.e., linear or uniform quantization. For any reference voltage that is greater than the voltage of signal Ain, the comparator 120 associated (i.e., connected) with that reference voltage asserts a corresponding one of binary signals C0 to Cx high to encoder 130. Encoder 130 provides digital output signal Dout with a value that depends on which of signals C0 to Cx are high. The digital signal Dout can then be processed, stored, and/or transmitted. The number (x+1) of comparators 120 in ADC 100 depends exponentially on the number (n) of bits in signal Dout. Accordingly, for applications requiring a large number of bits, ADC 100 requires many comparators, and the circuit area and power required for ADC 100 can be significant.
DACs are used to reconstruct the analog signal from a digital input signal Din and are generally less complex than ADCs. FIG. 2 shows a DAC 200 including reference voltage source 110, a decoder 230 that receives digital input signal Din, and transistors 220 coupled between reference voltages V0 to Vx and a terminal for a reconstructed analog output signal Aout. To perform a digital-to-analog conversion, decoder 230 receives digital input signal Din and selects and turns on the one of transistors 220 that corresponds to the value of signal Din. Accordingly, analog output signal Aout has a voltage equal to the one of reference voltages V0 to Vx that corresponds to the selected transistor 220.
Many other implementations of ADCs and DACs are known, such as switched capacitance and successive approximation techniques. Generally, these converters require substantial overhead and circuit area. In particular, when an analog-to-analog conversion is desired, a suitable converter circuit first uses an ADC to convert an analog input Ain to a digital output Dout. This digital output is then used as the digital input to a DAC for conversion to the desired analog signal Aout. Thus, both an ADC and a DAC are needed, thereby further increasing the overhead and circuit area of the analog-to-analog converter.
If the desired analog-to-analog conversion is not a one-to-one mapping, the reconstructed analog signal Aout is typically not an exact replica of the original analog signal Ain, which may be due to errors introduced during transmission or quantization. In general, the more levels M (x+1) of available quantized values, the less quantization error is present in the reconstructed analog signal. However, large numbers of levels require higher transmission bandwidths and may be impractical to implement due to system constraints on components of such an ADC. Furthermore, quantization errors may have more severe effects in certain applications, such as voice or audio transmission or recordation. Assuming audible or recognizable speech requires a minimum signal-to-noise (S/N) ratio, low voice signals are more susceptible to quantization errors than loud voice signals. Furthermore, voice signals are much more likely to have voltage amplitudes near zero, i.e., most voice signals are low voltage signals with only occasional bursts near the high end, which results in the adverse effects of quantization errors occurring much more frequently during a speech transmission or recording. Also, human hearing is more sensitive to low amplitude than high amplitude voice signals. Therefore, a linear mapping of input voltages to output voltages for analog-to-digital conversion can introduce substantial errors in low amplitude voice signals such that the subsequent digital-to-analog conversion results in an unacceptable speech quality.
As is well known, by using non-linear mapping, non-uniform quantization of input voltages to output voltages, soft voice signals are converted to signals that have a proportionally higher resolution per quantized level than loud voice signals in order to achieve a more optimum S/N ratio across the dynamic range of the voice signal. Non-uniform quantization can be achieved by first compressing the analog signal according to a logarithmic expression, such as a .mu.-law or A-law compression characteristic, and then uniformly quantizing the signal. A normalized curve of a .mu.-law compression, with .mu.=255, is shown in FIG. 3. (Note that only the positive quadrant is shown. The curve is symmetrical, such that negative input voltages have negative output voltages with the same characteristic curve as for positive input voltages.) With uniform quantization, it is seen from FIG. 3 that the compressed output is sampled at much shorter steps when the input signal is low and at increasingly longer steps when the input signal is high. The result is a signal in which low amplitude voltages have less quantization error and high amplitude voltages have more quantization error, which is acceptable for voice or speech applications. After compression and quantization (A/D conversion), the digital signal is transmitted over or recorded on a suitable medium. The digital signal is then converted back to analog (D/A conversion) and expanded through the inverse of the compression characteristic to restore the signal to the correct relative analog voltage levels.
As a result, circuits which perform companding (companders) are important in audio signal processing for increasing the overall S/N ratio and reducing the quantization error of low amplitude voice signals, which is the dominant portion of the voice signal range. However, many conventional companders can be relatively large and/or expensive and complicated, such as binary-weighted capacitor arrays using charge redistribution or ADC 100 (FIG. 1) and DAC 200 (FIG. 2) with precise different resistances for resistors R0 to Rx. For example, to implement a logarithmic compression with ADC 100, the low reference voltages need to be precise with small voltage differences between successive reference voltages in order to accurately compress low amplitude analog signals. Consequently, the resistances of the corresponding resistors must be precisely maintained and track each other due to process, temperature, and power supply variations, which can increase both the cost and complexity of the ADC.